AbstractCom­bined ther­apy made of a chemother­apy and an­tian­gio­genic agents is a clin­i­cal treat­ment rec­om­mended for its ef­fi­ciency. Since the op­ti­miza­tion of a treat­ment against can­cer re­lasp is still mostly based on on­col­o­gist’s know-how, it is de­sir­able to de­velop dif­fer­ent ap­proaches for such a task. Math­e­mat­i­cal mod­el­ling is one of the promis­ing ways. We here in­ves­ti­gated the ac­tion of a com­bined ther­apy in­serted to a math­e­mat­i­cal can­cer model in or­der to de­ter­mine how the dy­nam­ics un­der­ly­ing tu­mor growth is gov­erned by some key pa­ra­me­ters. We here re­tained a chemother­apy (for in­stance, pa­cli­taxel and car­bo­platin) com­bined with an an­tian­gio­genic drug (as be­va­cizumab) ap­plied to a can­cer model de­scrib­ing the in­ter­ac­tions be­tween host, im­mune, tu­mor and en­dothe­lial cells. The ef­fects of such a ther­apy are in­ves­ti­gated and the rel­e­vant role played by the “nor­mal” tis­sue of the tu­mor mi­cro-en­vi­ron­ment is ev­i­denced.

AbstractBackground : The use of web-based monitoring for lung cancer patients is growing in interest because of promising recent results suggesting improvement in cancer and resource utilization outcomes. It remains an open question whether the overall survival (OS) in these patients could be improved by using a web-mediated follow-up rather than classical scheduled follow-up and imaging.
Methods : Advanced-stage lung cancer patients without evidence of disease progression after or during initial treatment were randomly assigned in a multicenter phase III trial to compare a web-mediated follow-up algorithm (experimental arm), based on weekly self-scored patient symptoms, with routine follow-up with CT scans scheduled every three to six months according to the disease stage (control arm). In the experimental arm, an alert email was automatically sent to the oncologist when self-scored symptoms matched predefined criteria. The primary outcome was OS.
Results : From June 2014 to January 2016, 133 patients were enrolled and 121 were retained in the intent-to-treat analysis ; 12 deemed ineligible after random assignment were not subsequently followed. Most of the patients (95.1%) had stage III or IV disease. The median follow-up was nine months. The median OS was 19.0 months (95% confidence interval [CI] = 12.5 to noncalculable) in the experimental and 12.0 months (95% CI = 8.6 to 16.4) in the control arm (one-sided p = .001) (hazard ratio = 0.32, 95% CI = 0.15 to 0.67, one-sided p = .002). The performance status at first detected relapse was 0 to 1 for 75.9% of the patients in the experimental arm and for 32.5% of those in the control arm (two-sided p < .001). Optimal treatment was initiated in 72.4% of the patients in the experimental arm and in 32.5% of those in the control arm (two-sided p < .001).
Conclusions : A web-mediated follow-up algorithm based on self-reported symptoms improved OS due to early relapse detection and better performance status at relapse.

AbstractIf recent advances in oncology emphasized the role of microenvironment in tumor growth, the role of delays for modeling tumor growth is still uncertain. In this paper, we considered a model, describing the interactions of tumor cells with their microenvironment made of immune cells and host cells, in which we inserted, as suggested by the clinicians, two time delays, one in the interactions between tumor cells and immune cells and, one in the action of immune cells on tumor cells. We showed analytically that the singular point associated with the co-existence of the three cell populations loses its stability via a Hopf bifurcation. We analytically calculated a range of the delays over which tumor cells are inhibited by immune cells and over which a period-1 limit cycle induced by this Hopf bifurcation is observed. By using a global modeling technique, we investigated how the dynamics observed with two delays can be reproduced by a similar model without delays. The effects of these two delays was thus interpreted in terms of interactions between the cell populations.

AbstractIt is well known that cancers are significantly more often encountered in some tissues than in other ones. In this paper, by using a deterministic model describing the interactions between host, effector immune and tumor cells at the tissue level, we show that this can be explained by the dependency of tumor growth on parameter values characterizing the type as well as the state of the tissue considered due to the “way of life” (environmental factors, food consumption, drinking or smoking habits, etc.). Our approach is purely deterministic and, consequently, the strong correlation (r = 0.99) between the number of detectable growing tumors and the growth rate of cells from the nesting tissue can be explained without evoking random mutation arising during DNA replications in nonmalignant cells or “bad luck”. Strategies to limit the mortality induced by cancer could therefore be well based on improving the way of life, that is, by better preserving the tissue where mutant cells randomly arise.
Chaos, 27, 093101, 2017. Online

C. LetellierIntermittency as a transition to turbulence in pipes : A long tradition from Reynolds to the 21st century
Comptes Rendus de Mécanique, 345 (9), 642-659, 2017. Online

AbstractIntermittencies are commonly observed in fluid mechanics, and particularly, in pipe flows. Initially observed by Reynolds (1883), it took one century for reaching a rather full understanding of this phenomenon whose irregular dynamics (apparently stochastic) puzzled hydrodynamicists for decades. In this brief (non-exhaustive) review, mostly focused on the experimental characterization of this transition between laminar and turbulent regimes, we present some key contributions for evidencing the two concomittant and antagonist processes that are involved in this complex transition and were suggested by Reynolds. It is also shown that a clear explicative model was provided, based on the nonlinear dynamical systems theory, the experimental observations in fluid mechanics only providing an applied example, due to its obvious generic nature. [2]

This paper belongs to the volume A century of fluid mechanics : 1870–1970 presented by François Charru.

AbstractObservability is the property that enables recovering the state of a dynamical system from a reduced number of measured variables. In high-dimensional systems, it is therefore important to make sure that the variable recorded to perform the analysis conveys good observability of the system dynamics. The observability of a network of neuron models depends nontrivially on the observability of the node dynamics and on the topology of the network. The aim of this paper is twofold. First, to perform a study of observability using four well-known neuron models by computing three different observability coefficients. This not only clarifies observability properties of the models but also shows the limitations of applicability of each type of coefficients in the context of such models. Second, to study the emergence of phase synchronization in networks composed of neuron models. This is done performing multivariate singular spectrum analysis which, to the best of the authors’ knowledge, has not been used in the context of networks of neuron models. It is shown that it is possible to detect phase synchronization : (i) without having to measure all the state variables, but only one (that provides greatest observability) from each node and (ii) without having to estimate the phase.

AbstractSynchronization is a very generic process commonly observed in a large variety of dynamical systems which, however, has been rarely addressed in systems with low dissipation. Using the Rössler, the Lorenz 84, and the Sprott A systems as paradigmatic examples of strongly, weakly, and non-dissipative chaotic systems, respectively, we show that a parameter or frequency mismatch between two coupled such systems does not affect the synchronizability and the underlying structure of the joint attractor in the same way. By computing the Shannon entropy associated with the corresponding recurrence plots, we were able to characterize how two coupled nonidentical chaotic oscillators organize their dynamics in different dissipation regimes. While for strongly dissipative systems, the resulting dynamics exhibits a Shannon entropy value compatible with the one having an average parameter mismatch, for weak dissipation synchronization dynamics corresponds to a more complex behavior with higher values of the Shannon entropy. In comparison, conservative dynamics leads to a less rich picture, providing either similar chaotic dynamics or oversimplified periodic ones.